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Shadow-based matching for precise and robust absolute self-localization during lunar landings

机译:基于阴影的匹配,可在登月期间进行精确而强大的绝对自定位

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In this work, we use shadows as predictable landmarks for accurate and robust absolute self-localization during lunar landing. Due to the lack of an atmosphere, shadows on the moon are not diffused and therefore sharper than on Earth. This enables easy pre-computation of their appearance. By matching descent images from a lander's camera with reference images, rendered from available Digital Elevation Models (DEM), and the known sun position during the landing, we perform an estimation of the position. This serves as an input to a vision based navigation system. We first segment the shadows from the image content with adaptive binary thresholding, resulting in a binary shadow image. We have developed an enhanced shadow descriptor to depict a shadow's neighborhood by mapping the constellation of adjacent shadow centroids to a multilayer binary grid. This allows a time efficient and robust matching, which is further enhanced by a RANSAC based outlier detection. To test our method with the perturbations expected during the final phase of an actual lunar mission, particularly time and position deviation from the planned trajectory, we used DEMs of three different landing sites. Two of them were shadow abundant and one contained only a small amount of shadows. For each DEM, our method was separately tested with a position drift of up to 400m and a time drift of up to 50 min between the reference images and the descent images. The time drift was simulated by changing the position of the sun proportionally. With a maximum drift in position and time and at distances to the surface between 4km and 1 km, more than 90% of the shadows were matched correctly at the shadow abundant landing sites. It resulted in an accuracy of at least 1m for the position estimate. At least 40% correct matches were found for the landing site poor in shadows at distances to the surface between 36km and 12 km, resulting in an accuracy of the pose estimation with the same relative magnitude as bef- re, but with less reliability. Overall, for both altitude ranges the accuracy of the position estimate was 1% of the distance to surface or better.
机译:在这项工作中,我们将阴影用作可预测的地标,以在登月期间进行准确而强大的绝对自定位。由于缺乏大气,月球上的阴影不会扩散,因此比地球上的阴影更锐利。这样可以很容易地对其外观进行预计算。通过将着陆器摄像机的下降图像与从可用数字高程模型(DEM)渲染的参考图像和着陆过程中已知的太阳位置进行匹配,我们可以估算出该位置。这用作基于视觉的导航系统的输入。我们首先使用自适应二进制阈值对图像内容中的阴影进行分割,从而生成二进制阴影图像。我们已经开发了一种增强的阴影描述符,通过将相邻阴影质心的星座映射到多层二进制网格来描述阴影的邻域。这允许时间高效且鲁棒的匹配,通过基于RANSAC的离群值检测进一步增强了匹配。为了在实际登月任务的最后阶段预期的扰动(尤其是与计划轨迹的时间和位置偏差)之间测试我们的方法,我们使用了三个不同着陆点的DEM。其中两个阴影丰富,一个仅包含少量阴影。对于每个DEM,我们的方法都经过了分别在参考图像和下降图像之间的最大400m位置漂移和最大50分钟的时间漂移​​测试。通过按比例更改太阳的位置来模拟时间漂移。由于位置和时间的最大漂移以及与地面之间的距离在4 km和1 km之间,超过90%的阴影在阴影丰富的着陆点正确匹配。位置估计的精度至少为1m。在距地面36 km至12 km处阴影较差的着陆点,至少找到40%正确匹配,从而导致姿态估计的准确性与相对大小相同,但可靠性较低。总体而言,对于两个海拔范围,位置估计的精度均为距地面距离的1%或更高。

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